Deep learning assisted peak curation for large scale LC-MS Metabolomics

Available automated methods for peak detection in untargeted metabolomics suffer from poor precision. We present NeatMS which uses machine learning to replace peak curation by human experts. We show how to integrate our open source module into different LC-MS analysis workflows and quantify its performance. NeatMS is designed to be suitable for large scale studies and improves the robustness of the final peak list

Venn diagrams may indicate erroneous statistical reasoning in transcriptomics

A common application of differential expression analysis is finding genes that are differentially expressed upon treatment in only one out of several groups of samples. One of the approaches is to test for significant difference in expression between treatment and control separately in the two groups, and then select genes that show statistical significance in one group only. This approach is then often combined with a gene set enrichment analysis to find pathways and gene sets regulated by treatment in only this group. Here we show that this procedure is statistically incorrect and that the interaction between treatment and group should be tested instead. Moreover, we show that gene set enrichment analysis applied to such incorrectly defined genes group-specific genes may result in misleading artifacts. Due to the presence of false negatives, genes significant in one, but not the other group are enriched in gene sets which correspond to the overall effect of the treatment. Thus, the results appear related to the problem at hand, but do not reflect the group-specific effect of a treatment. A literature search revealed that more than a quarter of papers which used a Venn diagram to illustrate the results of separate differential analysis have also applied this incorrect reasoning

Search for markers of invasive growth in breast cancer: association with disease prognosis

In the present study, we analyzed the gene expression profiles of various morphological structures of breast cancer (GEO, GSE80754) to identify new markers of invasion and to assess their association with disease prognosis. Nine proteins (KIF14, DSC3, WAVE, etc.) was selected based on the literature analysis of the involvement of genes up- and down-regulated in solid and trabecular structures in cancer invasion and a heterogeneity in expression of their proteins in breast tumors. The association of these proteins with patients' survival was assessed

miRNAs from inflamed gingiva link gene signaling to increased MET expression

Several array-based microRNA (miRNA) expression studies independently showed increased expression of miRNAs hsa-miR-130a-3p, -142-3p, -144-3p, -144-5p, -223-3p, -17-5p, and -30e-5p in gingiva affected by periodontal inflammation. We aimed to determine direct target genes and signaling pathways regulated by these miRNAs to identify processes relevant to gingival inflammatory responses and tissue homeostasis. We transfected miRNA mimics (mirVana) for each of the 7 miRNAs separately into human primary gingival fibroblasts cultured from 3 different donors. Following RNA sequencing, differential gene expression and second-generation gene set enrichment analyses were performed. miRNA inhibition and upregulation was validated at the transcript and protein levels using quantitative reverse transcriptase polymerase chain reaction, Western blotting, and reporter gene assays. All 7 miRNAs significantly increased expression of the gene MET proto-oncogene, receptor tyrosine kinase (MET). Expression of known periodontitis risk genes CPEB1, ABCA1, and ATP6V1C1 was significantly repressed by hsa-miR-130a-3p, -144-3p, and -144-5p, respectively. The genes WASL, ENPP5, ARL6IP1, and IDH1 showed the most significant and strongest downregulation after hsa-miR-142-3p, -17-5p, -223-3p, and -30e-5p transfection, respectively. The most significantly regulated gene set of each miRNA related to cell cycle (hsa-miRNA-144-3p and -5p [P(adj) = 4 × 10(-40) and P(adj) = 4 × 10(-6)], -miR-17-5p [P(adj) = 9.5 × 10(-23)], -miR-30e-5p [P(adj) = 8.2 × 10(-18)], -miR-130a-3p [P(adj) = 5 × 10(-15)]), integrin cell surface interaction (-miR-223-3p [P(adj) = 2.4 × 10(-7)]), and interferon signaling (-miR-142-3p [P(adj) = 5 × 10(-11)]). At the end of acute inflammation, gingival miRNAs bring together complex regulatory networks that lead to increased expression of the gene MET. This underscores the importance of mesenchymal cell migration and invasion during gingival tissue remodeling and proliferation in restoring periodontal tissue homeostasis after active inflammation. MET, a receptor of the mitogenic hepatocyte growth factor fibroblast secreted, is a core gene of this process

Good Random Matrices over Finite Fields

The random matrix uniformly distributed over the set of all m-by-n matrices over a finite field plays an important role in many branches of information theory. In this paper a generalization of this random matrix, called k-good random matrices, is studied. It is shown that a k-good random m-by-n matrix with a distribution of minimum support size is uniformly distributed over a maximum-rank-distance (MRD) code of minimum rank distance min{m,n}-k+1, and vice versa. Further examples of k-good random matrices are derived from homogeneous weights on matrix modules. Several applications of k-good random matrices are given, establishing links with some well-known combinatorial problems. Finally, the related combinatorial concept of a k-dense set of m-by-n matrices is studied, identifying such sets as blocking sets with respect to (m-k)-dimensional flats in a certain m-by-n matrix geometry and determining their minimum size in special cases.Comment: 25 pages, publishe

The Equation of State and the Hugoniot of Laser Shock-Compressed Deuterium

The equation of state and the shock Hugoniot of deuterium are calculated using a first-principles approach, for the conditions of the recent shock experiments. We use density functional theory within a classical mapping of the quantum fluids [ Phys. Rev. Letters, {\bf 84}, 959 (2000) ]. The calculated Hugoniot is close to the Path-Integral Monte Carlo (PIMC) result. We also consider the {\it quasi-equilibrium} two-temperature case where the Deuterons are hotter than the electrons; the resulting quasi-equilibrium Hugoniot mimics the laser-shock data. The increased compressibility arises from hot $D^+-e$ pairs occuring close to the zero of the electron chemical potential.Comment: Four pages; One Revtex manuscript, two postscipt figures; submitted to PR

SODAR: managing multiomics study data and metadata

Scientists employing omics in life science studies face challenges such as the modeling of multiassay studies, recording of all relevant parameters, and managing many samples with their metadata. They must manage many large files that are the results of the assays or subsequent computation. Users with diverse backgrounds, ranging from computational scientists to wet-lab scientists, have dissimilar needs when it comes to data access, with programmatic interfaces being favored by the former and graphical ones by the latter. We introduce SODAR, the system for omics data access and retrieval. SODAR is a software package that addresses these challenges by providing a web-based graphical user interface for managing multiassay studies and describing them using the ISA (Investigation, Study, Assay) data model and the ISA-Tab file format. Data storage is handled using the iRODS data management system, which handles large quantities of files and substantial amounts of data. SODAR also offers programmable APIs and command-line access for metadata and file storage. SODAR supports complex omics integration studies and can be easily installed. The software is written in Python 3 and freely available at https://github.com/bihealth/sodar-server under the MIT license

Robust detection of clinically relevant features in single-cell RNA profiles of patient-matched fresh and formalin-fixed paraffin-embedded (FFPE) lung cancer tissue

PURPOSE: Single-cell transcriptional profiling reveals cell heterogeneity and clinically relevant traits in intra-operatively collected patient-derived tissue. So far, single-cell studies have been constrained by the requirement for prospectively collected fresh or cryopreserved tissue. This limitation might be overcome by recent technical developments enabling single-cell analysis of FFPE tissue. METHODS: We benchmark single-cell profiles from patient-matched fresh, cryopreserved and archival FFPE cancer tissue. RESULTS: We find that fresh tissue and FFPE routine blocks can be employed for the robust detection of clinically relevant traits on the single-cell level. Specifically, single-cell maps of fresh patient tissues and corresponding FFPE tissue blocks could be integrated into common low-dimensional representations, and cell subtype clusters showed highly correlated transcriptional strengths of signaling pathway, hallmark, and clinically useful signatures, although expression of single genes varied due to technological differences. FFPE tissue blocks revealed higher cell diversity compared to fresh tissue. In contrast, single-cell profiling of cryopreserved tissue was prone to artifacts in the clinical setting. CONCLUSION: Our analysis highlights the potential of single-cell profiling in the analysis of retrospectively and prospectively collected archival pathology cohorts and increases the applicability in translational research

Generation of iPSC lines with SLC16A2:G401R or SLC16A2 knock out

The X-linked Allan-Herndon-Dudley syndrome (AHDS) is characterized by severely impaired psychomotor development and is caused by mutations in the SLC16A2 gene encoding the thyroid hormone transporter MCT8 (monocarboxylate transporter 8). By targeting exon 3 of SLC16A2 using CRISPR/Cas9 with single-stranded oligodeoxynucleotides as homology-directed repair templates, we introduced the AHDS patient missense variant G401R and a novel knock-out deletion variant (F400Sfs*17) into the male healthy donor hiPSC line BIHi001-B. We successfully generated cerebral organoids from these genome-edited lines, demonstrating the utility of the novel lines for modelling the effects of MCT8-deficency on human neurodevelopment